LAUSR

Machine learning (ML) revolves around the concept of using experience to teach computer-based programs to reliably perform specific tasks. Healthcare setting is an ideal environment for adaptation of ML applications given the multiple specific tasks that could be allocated to computer programs to perform. There have been several scoping reviews published in literature looking at the general acceptance and adaptability of surgical specialities to ML applications, but very few focusing on the application towards craniofacial surgery. This study aims to present a detailed scoping review regarding the use of ML applications in craniofacial surgery.